Bio-IT FAIR Data Hackathon

MAY 18 – 19, 2026, IN BOSTON, MA

The Bio-IT FAIR Data Hackathon has become a cornerstone of the Bio-IT World Conference & Expo, bringing together data scientists, software developers, and life science professionals to address real-world data challenges. On May 18-19, 2026, the CFDE Training Center, managed by ORAU, proudly hosted the 7th Hackathon as part of the 25th Annual Bio-IT World Conference & Expo. Focused on Open Source and FAIR (Findable, Accessible, Interoperable, Reusable) data principles, this two-day event fostered innovation and collaboration to deliver creative and practical solutions.

Hackathon Sponsor:

CFDE

With six all-star project teams, the 2026 Hackathon showcased the incredible power of open science in action! Team members brought their impressive skills, knowledge, and enthusiasm to deliver projects that leveraged NIH Common Fund Data Ecosystem (CFDE) omics data and integrated CFDE tools.

Congratulations to this year's winning teams

1st Place: Exercise Mimetics Discovery with Gene Set Foundation Models (Project 6)

Exercise produces consistent molecular signatures across tissues, raising the question of whether existing compounds produce similar patterns. This project compared MoTrPAC exercise gene signatures with LINCS drug perturbation data to identify compounds with overlapping molecular effects. The team also explored Gene Set Foundation Models (GSFMs) to examine relationships among candidate compounds.
Team members included Charlie Hou, Genevieve Baddoo, Sai Sanjana Prakash, Justin Seyedmoomenkashi, Mrunali Thokadiwala, Rakesh Bantu

2nd Place: Visible Neural Networks for Cancer Drug Response (CellMap-VNN) (Project 3)

Predicting cancer drug response from molecular data remains a challenging problem. This project developed interpretable Visible Neural Networks that incorporated hierarchical cellular information such as protein–protein interactions and perturbation data. By grounding the model architecture in known biological structure, the team explored if this approach improved interpretability compared to conventional models.
Team members included Rachana Pandey, Mubin Modi, Sayuni Dharmasena

3rd Place: Exercise as Medicine: Opposing Molecular Signatures in Health and Disease (Project 1)

Exercise is known to influence many biological pathways, but how do those changes compare directly to what happens in disease? This project analyzed multi-omics data from the MoTrPAC endurance training study and compared it with publicly available rat disease models such as diabetes, hypertension, and cancer. The goal was to identify genes, proteins, and metabolites that shift in opposite directions in exercise versus disease contexts.
Team members included David Jimenez-Morales, Reva Shenwai, Oliver Abinader, Angela Ning, Elie Abi Khalil

Dream Team Award: Mining the CFDE for Post-Translational Modification Data (Project 5)

Post-translational modifications (PTMs) play a central role in regulating protein function and are frequently implicated in disease processes. This project identified PTM-relevant datasets within the CFDE and focused on analyzing connections among modified genes, associated diseases, and affected biological pathways. The team linked PTM-containing datasets to gene-level annotations and mapped these genes to known disease associations and pathway resources.
Team members included Vlado Dancik, Chase Yakaboski, Amy Reese, Jana Moubarak, Viveka Patil, Christina Akirtava

Nobody Panicked Award: CFDE-Data-Driven K nowledge Discovery, to Illuminate the Molecular Basis of Drug Side Effects (Project 4)

Drug side effects often reflect underlying biological mechanisms that are not fully understood. This project used DrugCentral and Pharos to identify drugs that share a side effect and may act on a common target. The team evaluated whether the target is expressed in relevant tissues and examined pathway databases such as Reactome to explore plausible mechanistic explanations.
Team members included Manjil Pradhan, Olaitan Awe, Antonia Kowalewski, Nerissa Vu

BLAST Award: Drug Repurposing Through Disease Similarity Analysis Using BiomarkerKB with other CFDE Resources and Tools (Project 2)

Many diseases share molecular biomarkers, which may point to shared biological mechanisms. This project integrated BiomarkerKB with CFDE datasets such as LINCS, IDG, and GTEx to explore disease similarity through network-based approaches. Participants constructed and analyzed a biomarker–drug knowledge graph to cluster diseases and identify potential repurposing candidates supported by multiple data sources.
Team members included Patrick McNeely, Yi-Chien Wu, Peter Fan, Prasanna Kharche, Anoushka Prabhu

Learn more about other CFDE Training Center events: https://orau.org/cfde-trainingcenter/events/events.html

Contact the CFDE Training Center for more details about the Hackathon: [email protected]